Method and system for virtual inspection and simulation of rare earth production process

Abstract

The present disclosure relates to a method and system for virtual inspection and simulation of a rare earth production process, and belongs to the field of digital twin technologies. According to the method, a virtual workshop is built based on a geometric model and a control script of a production site as well as real-time data of the site; and simulation of an entire process is completed. Visualized demonstration of data in each production process is realized by building a virtual rare earth workshop and establishing a data connection between an actual workshop and the virtual rare earth workshop. In addition, fast inspection of a production device is realized. In addition, contents of components are forecast based on historical data according to an extraction mechanism; and whether to give a warning is determined automatically based on the contents. Therefore, real-time and precise forecasting of a process index is realized.

What is claimed is: 
     
         1 . A method for virtual inspection and simulation of a rare earth production process, comprising:
 obtaining real-time data of a production site, wherein the real-time data comprises data of a process production index;   building a virtual rare earth workshop based on a geometric model and a control script of the production site as well as the real-time data, for a user to perform inspection;   obtaining historical data of the process production index;   optimizing an extraction mechanism model based on the historical data of the process production index according to a parameter optimization algorithm to obtain a data-driven model, wherein the extraction mechanism model is a mathematical model representing an extraction mechanism of rare earth;   obtaining process information input by the user;   forecasting a content of each element in a finished product of a process based on the process information by using the data-driven model; and   determining, based on the content of each element, whether to give a warning.   
     
     
         2 . The method for virtual inspection and simulation of a rare earth production process according to  claim 1 , wherein the optimizing an extraction mechanism model based on the historical data of the process production index according to a parameter optimization algorithm to obtain a data-driven model specifically comprises:
 optimizing a separation coefficient in the extraction mechanism model based on the historical data of the process production index according to a particle swarm optimization algorithm, to obtain the data-driven model.   
     
     
         3 . A system for virtual inspection and simulation of a rare earth production process, comprising: a control information system for rare earth production, a virtual workshop for rare earth production, and a digital twin service system, wherein
 the control information system for rare earth production is configured to obtain real-time data of a production site, and control a production process;   the virtual workshop for rare earth production is configured to build a virtual rare earth workshop based on a geometric model and a control script of the production site as well as the real-time data, for a user to perform inspection; and   the digital twin service system is configured to:   obtain historical data of a process production index;   optimize an extraction mechanism model based on the historical data of the process production index according to a parameter optimization algorithm to obtain a data-driven model, wherein the extraction mechanism model is a mathematical model representing an extraction mechanism of rare earth;   obtain process information input by the user;   forecast a content of each element in a finished product of a process based on the process information by using the data-driven model; and   determine, based on the content of each element, whether to give a warning.   
     
     
         4 . The system for virtual inspection and simulation of a rare earth production process according to  claim 3 , wherein the control information system for rare earth production comprises a basic control module and process detection modules, wherein
 the basic control module is configured to execute a control instruction;   the basic control module comprises a motor converter, a variable-flow pump, a metering pump, a solenoid valve, and a PLC, wherein the motor converter is configured to adjust a rotational speed of an agitator; the variable-flow pump and the metering pump are configured to control quantitative feeding in an extraction process; the solenoid valve is configured to control feeding and discharging of a feed solution; and the PLC is configured to obtain a control instruction, and transmit the control instruction to the motor converter, the variable-flow pump, the metering pump, and the solenoid valve;   the process detection module is configured to obtain real-time data; and   the process detection module comprises a flowmeter, a level gauge, a thermometer, a pH meter, and component content detection devices, wherein the flowmeter is configured to monitor and control a feeding flow rate and a discharging flow rate of the feed solution in an extraction process; the level gauge is configured to monitor and detect levels of liquid in an extraction tank and a storage tank; the thermometer and the pH meter are configured to prepare a scrubbing solution and an extraction solution that meet requirements for temperature and potential of hydrogen; and the component content detection devices are disposed for each detection level of a rare earth extraction process.   
     
     
         5 . The system for virtual inspection and simulation of a rare earth production process according to  claim 3 , further comprising:
 a twin database configured to store historical data, real-time data, and warning information.   
     
     
         6 . The system for virtual inspection and simulation of a rare earth production process according to  claim 5 , wherein the control information system for rare earth production further comprises a data transmission module configured to exchange data between the twin database and the control information system for rare earth production. 
     
     
         7 . The system for virtual inspection and simulation of a rare earth production process according to  claim 5 , wherein the virtual workshop for rare earth production comprises: a data exchanging module, a geometric model base, a user interaction module, and a scene changing module, wherein
 the data exchanging module is configured to regularly query related data in the twin database according to process-data correspondence;   the geometric model base is configured to build a virtual rare earth workshop, and visualize the virtual rare earth workshop, wherein the virtual rare earth workshop is built by using modeling software;   the user interaction module is configured to control a scene viewing angle when the user performs inspection, and a demo animation; and   the scene changing module is configured to change a virtual rare earth workshop when the user performs inspection.   
     
     
         8 . The system for virtual inspection and simulation of a rare earth production process according to  claim 3 , wherein the digital twin service system further comprises: a process optimization module configured to:
 obtain an optimization strategy by using an optimal control algorithm based on an objective set by the user, wherein the optimal control algorithm is used for optimal control over a flow rate of a reagent in extraction based on static setting and dynamic compensation.   
     
     
         9 . The system for virtual inspection and simulation of a rare earth production process according to  claim 8 , wherein the controlling a production process specifically comprises:
 controlling the production process according to the optimization strategy.   
     
     
         10 . The system for virtual inspection and simulation of a rare earth production process according to  claim 3 , wherein the digital twin service system further comprises a model updating module configured to:
 calculate an error between the forecast content and actual data of a process index, to obtain a content error; and   adjust the data-driven model based on the content error according to the parameter optimization algorithm.